About this book
In this new volume, renowned authors contribute fascinating, cutting-edge insights into microarray data analysis. Included in this innovative book are in-depth insights into presentations of genomic signal processing, artificial neural network use for microarray data analysis, signal processing and design of microarray time series experiments, application of regression methods, gene expression sprofiles and prognostic markers for primary breast cancer, and factors affecting the cross-correlation of gene expression profiles. Also detailed are use of tiling arrays for large genomes analysis, a comparative genomic hybridization data on cDNA microarrays, integrated high-resolution genome-wide analysis of gene dosage and gene expression in human brain tumors, gene and MeSH ontology, and predicting survival prediction in follicular lymphoma using tissue microarrays.
The protocols follow the successful Methods in Molecular Biology series format, offering step-by-step instructions, an introduction outlining the principles behind the technique, lists of the necessary equipment and reagents, and tips on troubleshooting and avoiding pitfalls.
Table of contents
Table of Contents
Chapter 1
Microarray Data Analysis: An Overview of Design, Methodology and Analysis
Ashani T. Weeraratna and Dennis D. Taub
Chapter 2
Genomic Signal Processing: From Matrix Algebra to Genetic Networks
Orly Alter
Chapter 3
Online Analysis of Microarray Data Using Artificial Neural Networks
Braden Greer and Javed Khan
Chapter 4
Signal Processing and the Design of Microarray Time Series Experiments
Robert R. Klevecz, Caroline M. Li and James L. Bolen
Chapter 5
Predictive Models of Gene Regulation: Application of Regression Methods to Microarray Data
Debopriya Das and Michael Q. Zhang
Chapter 6
Statistical Framework for Gene Expression Data Analysis
Olga Modlich and Marc Munnes
Chapter 7
Gene Expression Profiles and Prognostic Markers for Primary Breast Cancer
Yixin Wang, Jan Kljin, Yi Zhang, David Atkins and John Foekens
Chapter 8
Comparing microarray studies
Mayte Suárez-Fariñas and Marcelo O. Magnasco
Chapter 9
A Pitfall in Series of Microarrays: The Position of Probes Affects the Cross Correlation of Gene Expression Profiles
Gábor Balázsi and Zoltán N. Oltvai
Chapter 10
In Depth Query of Large Genomes using Tiling Arrays
Manoj Pratim Samanta, Waraporn Tongprasit and Viktor Stolc
Chapter 11
Analysis of Comparative Genomic Hybridization Data on cDNA Microarrays
Sven Bilke and Javed Khan
Chapter 12
Integrated high-resolution genome-wide analysis of gene dosage and gene expression in human brain tumors
Dejan Juric, Claudia Bredel, Branimir I. Sikic, and Markus Bredel
Chapter 13
Progression-Associated Genes in Astrocytoma Identified by Novel Microarray Gene Expression Data Reanalysis
Tobey J. MacDonald, Ian F. Pollack, Hideho Okada, Soumyaroop Bhattacharya, and James Lyons-Weiler
Chapter 14
Interpreting Microarray Results with Gene Ontology and MeSH Ontology
John D. Osborne, Lihua (Julie) Zhu, Simon M. Lin, and Warren A. Kibbe
Chapter 15
Incorporation of Gene Ontology Annotations to Enhance Microarray Data Analysis
Michael F. Ochs, Aidan J. Peterson, Andrew Kossenkov, and Ghislain Bidaut
Chapter 16
Predicting Survival in Follicular Lymphoma using Tissue Microarrays
Michael J. Korenberg, Pedro Farinha, and Randy D. Gascoyne